The present invention relates to a multiplying device, a linear algebraic processor, a neuromorphic processor, and and optical processor.
In the technical field of artificial intelligence, it is known to provide so-called "neural networks" which mimic the operation of small networks of neurons in an animal brain. Such neural networks include neuromorphic linear algebraic processors which are capable of being taught to perform various functions, for instance in the field of pattern recognition. The linear algebraic processors are required to perform vector matrix multiplications, effectively in parallel with the matrix elements being updated effectively in parallel for the purpose of teaching the network to perform its intended function.
Although it is possible to simulate the operation of a neural network by means of a conventional programmed data processor, the speed of operation is severely limited because of the essentially serial operation of such arrangements. In order to overcome this problem, dedicated electronic devices have been provided in which the matrix multiplication and updating of matrix elements are performed in parallel. Such devices may employ digital circuitry, in which the matrix elements are stored in binary format, or analog circuitry, in which conventional charge storage devices such as capacitors or charge coupled devices store the matrix elements. However, the semi-conductor devices of these types require relatively large silicon substrate areas for implementation and relatively large numbers interconnections for parallel updating.
Alternative type of processor is disclosed in an article entitled "GaAs/AlGaAs Optical Interconnection Chip for Neural Network" in the Japanese Journal of Applied Physics, Volume 28, No. 11, Nov. 1989, pages L2101 to L2103 by Y. Nitta, J. Ohta, K. Mitsunaga, M. Takahashi, S. Tai and K. Kyuma. The device disclosed in this article uses arrays of light emitters and facing light detectors separated by a fixed mask of transparent and opaque regions. The elements of an input vector are applied to strips of light emitters whereas the elements of the output vector are formed by orthogonal strips of light detectors. Light from each element of each strip emitter is modulated or attenuated by the mask before being received by a facing portion of an orthogonal light detector, so that the matrix elements for the matrix multiplications are formed by the light transmissive properties if the elements of the mask. Thus, this arrangement is capable of performing a fixed algebraic operation but, after manufacture, cannot be adapted or taught to perform other operations.